The Problem
Recipe data is spread across thousands of food blogs. Aggregating recipes, ingredients, and cooking instructions requires parsing inconsistent HTML or paying for recipe APIs.
How Scavio Helps
- Google search for recipe results with rich snippets
- YouTube cooking video search with transcripts
- Structured data from Knowledge Graph
- Build recipe recommendation engines
Relevant Platforms
Web search with knowledge graph, PAA, and AI overviews
YouTube
Video search with transcripts and metadata
Quick Start: Python Example
Here is a quick example searching Google for "healthy chicken dinner recipes under 30 minutes":
import requests
API_KEY = "your_scavio_api_key"
response = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={
"x-api-key": API_KEY,
"Content-Type": "application/json",
},
json={"query": query},
)
data = response.json()
for result in data.get("organic_results", [])[:5]:
print(f"{result['position']}. {result['title']}")
print(f" {result['link']}\n")Built for Food apps, recipe platforms, meal planning services
Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your recipe & food search solution. The API returns structured JSON that is ready for processing, analysis, or feeding into AI agents.
Start with the free tier (500 credits/month, no credit card required) and scale to paid plans when you need higher volume.